An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data

BACKGROUND: Rapid, preoperative identification of patients with the highest risk for medical complications is necessary to ensure that limited infrastructure and human resources are directed towards those most likely to benefit. Existing risk scores either lack specificity at the patient level or ut...

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Detalles Bibliográficos
Publicado en:Br J Anaesth
Autores principales: Hill, Brian L., Brown, Robert, Gabel, Eilon, Rakocz, Nadav, Lee, Christine, Cannesson, Maxime, Baldi, Pierre, Olde Loohuis, Loes, Johnson, Ruth, Jew, Brandon, Maoz, Uri, Mahajan, Aman, Sankararaman, Sriram, Hofer, Ira, Halperin, Eran
Formato: Artigo
Lenguaje:Inglês
Publicado: Elsevier 2019
Materias:
Quality and Patient Safety
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC6883494/
https://ncbi.nlm.nih.gov/pubmed/31627890
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.bja.2019.07.030
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